System and method for biometric retinal identification

Abstract

Retinal blood vessels are detected for biometric identification by: receiving at least one image with retinal data; detecting an area in the image corresponding to a spatial variation in the image; and determining a blood vessel pattern relative in the area. The spatial variation may be determined according to a spatial intensity gradient. The area corresponding to the spatial variation may be defined by a fitted shape. A specific embodiment determines a structural measurement, such as a structural center of mass, in the area, and the blood vessel pattern is determined relative to the structural measurement. The blood vessel pattern may be determined by identifying blood vessel cross sections within the area and linking the blood vessel cross sections to determine blood vessels. Furthermore, each of the blood vessel cross sections may be represented by an N-vector determined by a N-parameter non-linear fitting function or a linear function combination.

1 . A method for identifying retinal blood vessels for biometric identification, the method comprising: 
 receiving at least one image with retinal data;    detecting an area in the at least one image corresponding to a spatial variation in the at least one image; and    determining a blood vessel pattern in the area corresponding to the spatial variation in the at least one image.    
     
     
         2 . The method according to  claim 1 , wherein the step of detecting an area in the at least one image corresponding to a spatial variation in the at least one image includes detecting an area corresponding to a spatial intensity gradient.  
     
     
         3 . The method according to  claim 1 , further comprising defining the area corresponding to the spatial variation by a fitted shape.  
     
     
         4 . The method according to  claim 3 , wherein, in the step of defining the area corresponding to the spatial variation by a fitted shape, the fitted shape is expressed in a polar coordinate system.  
     
     
         5 . The method according to  claim 3 , wherein, in the step of defining the area corresponding to the spatial variation by a fitted shape, the fitted shape is expressed in a Cartesian coordinate system.  
     
     
         6 . The method according to  claim 3 , further comprising comparing the fitted shape to a threshold to determine an image quality.  
     
     
         7 . The method according to  claim 1 , further comprising: 
 determining a measure of focus and sharpness for the image; and    comparing the measure of focus and sharpness to a threshold to determine an image quality.    
     
     
         8 . The method according to  claim 1 , wherein the step of determining a blood vessel pattern comprises: 
 determining blood vessel cross sections within the area corresponding to the spatial variation in the at least one image; and    linking the blood vessel cross sections to determine blood vessels.    
     
     
         9 . The method according to  claim 8 , wherein the step of determining blood vessel cross sections within the area corresponding to the spatial variation in the at least one image includes representing each of the blood vessel cross sections by an N-vector determined from at least one of a N-parameter non-linear fitting function and a linear function combination.  
     
     
         10 . The method according to  claim 9 , wherein the step of representing each of the blood vessel cross sections by an N-vector includes fitting a non-linear five-parameter model to intensity profiles within the area according to a Levenberg-Marquardt method.  
     
     
         11 . The method according to  claim 10 , wherein, in the step of fitting a non-linear five-parameter model to intensity profiles within the area according to a Levenberg-Marquardt method, the intensity profiles are samples of a length along concentric ellipses at different radii.  
     
     
         12 . The method according to  claim 10 , wherein, in the step of fitting a non-linear five-parameter model to intensity profiles within the area according to a Levenberg-Marquardt method, the intensity profiles are samples of a length along two perpendicular axes.  
     
     
         13 . The method according to  claim 8 , further comprising determining bifurcations and locations of entry and exit for the blood vessels.  
     
     
         14 . The method according to  claim 1 , wherein, in the step of receiving at least one image with retinal data, the at least one image is an image bitmap.  
     
     
         15 . The method according to  claim 1 , wherein, in the step of receiving at least one image with retinal data, the at least one image is in a video frame of a camera with a field-of-view, and the step of detecting the area corresponding to the spatial variation comprises: 
 detecting an outer edge of the field-of-view of the camera; and    shrinking the outer edge non-uniformly until a spatial intensity gradient is detected.    
     
     
         16 . The method according to  claim 15 , wherein the step of detecting an outer edge of the field-of-view of the camera comprises: 
 determining horizontal, vertical, and angular projections of gradient of the video frame; and    applying local edge detection.    
     
     
         17 . The method according to  claim 1 , further comprising checking the blood vessel pattern for at least one of a minimum number of vessels, a minimum path length of detected blood vessels, and a minimum number of at least one of bifurcations and entry/exit points to determine a retina code quality.  
     
     
         18 . The method according to  claim 1 , further comprising storing the blood vessel pattern to enroll the image for biometric identification.  
     
     
         19 . The method according to  claim 1 , further comprising comparing the blood vessel pattern with a reference blood vessel pattern for biometric identification.  
     
     
         20 . The method according to  claim 19 , further comprising, before comparing the blood vessel pattern with a reference blood vessel pattern, normalizing the blood vessel pattern and the reference blood vessel pattern.  
     
     
         21 . The method according to  claim 20 , wherein the step of normalizing the blood vessel pattern and the reference blood vessel pattern includes encoding a region around each blood vessel in the blood vessel pattern as a template bitmap.  
     
     
         22 . The method according to  claim 20 , wherein the step of normalizing the blood vessel pattern and the reference blood vessel pattern includes encoding a single region defined about a center.  
     
     
         23 . The method according to  claim 19 , further comprising, before comparing the blood vessel pattern with a reference blood vessel pattern, correcting for displacement between the blood vessel pattern and the reference blood vessel pattern.  
     
     
         24 . The method according to  claim 23 , wherein the step of correcting for displacement between the blood vessel pattern and the reference blood vessel pattern includes aligning blood vessels directly.  
     
     
         25 . The method according to  claim 24 , wherein the step of aligning blood vessels directly includes determining vessel-by-vessel comparisons of distance.  
     
     
         26 . The method according to  claim 24 , wherein the step of aligning blood vessels directly includes applying rigid-body transformations.  
     
     
         27 . The method according to  claim 19 , wherein the step of comparing the blood vessel pattern with a reference blood vessel pattern comprises comparing encodings for the blood vessel pattern and the reference blood vessel pattern.  
     
     
         28 . The method according to  claim 19 , wherein the step of comparing the blood vessel pattern with a reference blood vessel pattern comprises comparing vessel cross sections between the blood vessel pattern and the reference blood vessel pattern.  
     
     
         29 . The method according to  claim 1 , further comprising the step of determining a structural measurement in the area corresponding to the spatial variation, wherein the step of determining a blood vessel pattern in the area comprises determining a blood vessel pattern in the area relative to the structural measurement.  
     
     
         30 . The method according to  claim 29 , wherein the step of determining a structural measurement in the area corresponding to the spatial variation includes determining a structural center of mass in the area corresponding to the spatial variation.  
     
     
         31 . The method according to  claim 29 , wherein the step of determining a blood vessel pattern comprises: 
 determining blood vessel cross sections within the area relative to the structural measurement; and    linking the blood vessel cross sections to determine blood vessels.    
     
     
         32 . The method according to  claim 29 , further comprising comparing the structural measurement to a threshold to determine an image quality.  
     
     
         33 . A system for identifying retinal blood vessels for biometric identification, the system comprising: 
 means for receiving at least one image with retinal data;    means for detecting an area in the at least one image corresponding to a spatial variation in the at least one image; and    means for determining a blood vessel pattern in the area corresponding to the spatial variation in the at least one image.    
     
     
         34 . The system according to  claim 33 , wherein the means for detecting an area in the-at least one-image corresponding to a spatial variation in the at least one image includes means for detecting an area corresponding to a spatial intensity gradient.  
     
     
         35 . The system according to  claim 33 , further comprising means for defining the area corresponding to the spatial variation by a fitted shape.  
     
     
         36 . The system according to  claim 35 , wherein the fitted shape is expressed in a polar coordinate system.  
     
     
         37 . The system according to  claim 35 , wherein the fitted shape is expressed in a Cartesian coordinate system.  
     
     
         38 . The system according to  claim 35 , further comprising means for comparing the fitted shape to a threshold to determine an image quality.  
     
     
         39 . The system according to  claim 33 , further comprising: 
 means for determining a measure of focus and sharpness for the image; and    means for comparing the measure of focus and sharpness to a threshold to determine an image quality.    
     
     
         40 . The system according to  claim 33 , wherein the means for determining a blood vessel pattern comprises: 
 means for determining blood vessel cross sections within the area corresponding to the spatial variation in the at least one image; and    means for linking the blood vessel cross sections to determine blood vessels.    
     
     
         41 . The system according to  claim 40 , wherein the means for determining blood vessel cross sections within the area corresponding to the spatial variation in the at least one image includes means for representing each of the blood vessel cross sections by an N-vector determined from at least one of a N-parameter non-linear fitting function and a linear function combination.  
     
     
         42 . The system according to  claim 41 , wherein the means for representing each of the blood vessel cross sections by an N-vector includes means for fitting a non-linear five-parameter model to intensity profiles within the area according to a Levenberg-Marquardt system.  
     
     
         43 . The system according to  claim 42 , wherein the intensity profiles are samples of a length along concentric ellipses at different radii.  
     
     
         44 . The system according to  claim 42 , wherein the intensity profiles are samples of a length along two perpendicular axes.  
     
     
         45 . The system according to  claim 40 , further comprising means for determining bifurcations and locations of entry/exit points for the blood vessels.  
     
     
         46 . The system according to  claim 33 , wherein the at least one image is an image bitmap.  
     
     
         47 . The system according to  claim 33 , wherein the at least one image is in a video frame of a camera with a field-of-view, and the means for detecting the area corresponding to the spatial variation comprises: 
 means for detecting an outer edge of the field-of-view of the camera; and    means for shrinking the outer edge non-uniformly until a spatial intensity gradient is detected.    
     
     
         48 . The system according to  claim 47 , wherein the means for detecting an outer edge of the field-of-view of the camera comprises: 
 means for determining horizontal, vertical, and angular projections of gradient of the video frame; and    means for applying local edge detection.    
     
     
         49 . The system according to  claim 33 , further comprising means for checking the blood vessel pattern for at least one of a minimum number of vessels, a minimum path length of detected blood vessels, and a minimum number of at least one of bifurcations and entry/exit points to determine a retina code quality.  
     
     
         50 . The system according to  claim 33 , further comprising means for storing the blood vessel pattern to enroll the image for biometric identification.  
     
     
         51 . The system according to  claim 33 , further comprising means for comparing the blood vessel pattern with a reference blood vessel pattern for biometric identification.  
     
     
         52 . The system according to  claim 51 , further comprising means for normalizing the blood vessel pattern and the reference blood vessel pattern.  
     
     
         53 . The system according to  claim 52 , wherein the means for normalizing the blood vessel pattern and the reference blood vessel pattern includes means for encoding a region around each blood vessel in the blood vessel pattern as a template bitmap.  
     
     
         54 . The system according to  claim 53 , wherein the step of normalizing the blood vessel pattern and the reference blood vessel pattern includes encoding a single region defined about a center.  
     
     
         55 . The system according to  claim 53 , further comprising means for correcting for displacement between the blood vessel pattern and the reference blood vessel pattern.  
     
     
         56 . The system according to  claim 55 , wherein the means for correcting for displacement between the blood vessel pattern and the reference blood vessel pattern includes means for aligning blood vessels directly.  
     
     
         57 . The system according to  claim 56 , wherein the means for aligning blood vessels directly includes means for determining vessel-by-vessel comparisons of distance.  
     
     
         58 . The system according to  claim 56 , wherein the means for aligning blood vessels directly includes means for applying rigid-body transformations.  
     
     
         59 . The system according to  claim 51 , wherein the means for comparing the blood vessel pattern with a reference blood vessel pattern comprises means for comparing encodings for the blood vessel pattern and the reference blood vessel pattern.  
     
     
         60 . The system according to  claim 51 , wherein the means for comparing the blood vessel pattern with a reference blood vessel pattern comprises means for comparing vessel cross sections between the blood vessel pattern and the reference blood vessel pattern.  
     
     
         61 . The system according to  claim 33 , further comprising the means for determining a structural measurement in the area corresponding to the spatial variation, wherein the means for determining a blood vessel pattern in the area comprises means for determining a blood vessel pattern in the area relative to the structural measurement.  
     
     
         62 . The system according to  claim 61 , wherein the means for determining a structural measurement in the area corresponding to the spatial variation includes means for determining a structural center of mass in the area corresponding to the spatial variation.  
     
     
         63 . The system according to  claim 61 , wherein the means for determining a blood vessel pattern comprises: 
 means for determining blood vessel cross sections within the area relative to the structural measurement; and    means for linking the blood vessel cross sections to determine blood vessels.    
     
     
         64 . The system according to  claim 61 , further comprising means for comparing the structural measurement to a threshold to determine an image quality.